Physical Sciences and Mathematics Commons^™

Impact Of Difficult Negatives On Twitter Crisis Detection, Yuhao Zhang, Siaw Ling Lo, Phyo Yi Win Myint

Research Collection School Of Computing and Information Systems

Twitter has become an alternative information source during a crisis. However, the short, noisy nature of tweets hinders information extraction. While models trained with standard Twitter crisis datasets accomplished decent performance, it remained a challenge to generalize to unseen crisis events. Thus, we proposed adding “difficult” negative examples during training to improve model generalization for Twitter crisis detection. Although adding random noise is a common practice, the impact of difficult negatives, i.e., negative data semantically similar to true examples, was never examined in NLP. Most of existing research focuses on the classification task, without considering the primary information need of …

Champions For Social Good: How Can We Discover Social Sentiment And Attitude-Driven Patterns In Prosocial Communication?, Raghava Rao Mukkamala, Robert J. Kauffman, Helle Zinner Henriksen

Research Collection School Of Computing and Information Systems

The UN High Commissioner on Refugees (UNHCR) is pursuing a social media strategy to inform people about displaced populations and refugee emergencies. It is actively engaging public figures to increase awareness through its prosocial communications and improve social informedness and support for policy changes in its services. We studied the Twitter communications of UNHCR social media champions and investigated their role as high-profile influencers. In this study, we offer a design science research and data analytics framework and propositions based on the social informedness theory we propose in this paper to assess communication about UNHCR’s mission. Two variables—refugee-emergency and champion …

Storm The Capitol: Linking Offline Political Speech And Online Twitter Extra-Representational Participation On Qanon And The January 6 Insurrection, Claire Seungeun Lee, Juan Merizalde, John D. Colautti, Jisun An, Haewoon Kwak

Research Collection School Of Computing and Information Systems

The transfer of power stemming from the 2020 presidential election occurred during an unprecedented period in United States history. Uncertainty from the COVID-19 pandemic, ongoing societal tensions, and a fragile economy increased societal polarization, exacerbated by the outgoing president's offline rhetoric. As a result, online groups such as QAnon engaged in extra political participation beyond the traditional platforms. This research explores the link between offline political speech and online extra-representational participation by examining Twitter within the context of the January 6 insurrection. Using a mixed-methods approach of quantitative and qualitative thematic analyses, the study combines offline speech information with Twitter …

Law Library Blog (January 2022): Legal Beagle's Blog Archive, Roger Williams University School Of Law

Law Library Newsletters/Blog

No abstract provided.

Tweets R Us: Predicting Personality From Language And Emoji Use On Twitter, Maxwell Meckling, Sarah Shoup, D. E. Chan-Tin, Shelia Kennison

Computer Science: Faculty Publications and Other Works

The research investigated the suggestion from prior research that language and emojis use on Twitter and other social media platforms can predict users’ personality and gender (Adali et al., 2014; Golbeck et al., 2011; Li et al., 2019; Moreno et al., 2019; Raess, 2018). Some studies have also analyzed Twitter language to identify individuals with specific health conditions (e.g., alcohol recovery, Golbeck, 2012; sleep problems, Suarez et al., 2018).

If strategies to predict Twitter users’ characteristics prove to be successful, future efforts to direct persuasive messages related to recommended practices in public health and/or cybersecurity will be possible. Commercial applications …

Does Active Service Intervention Drive More Complaints On Social Media? The Roles Of Service Quality And Awareness, Shujing Sun, Yang Gao, Huaxia Rui

Research Collection School Of Computing and Information Systems

Despite many advantages of social media as a customer service channel, there is a concern that active service intervention encourages excessive service complaints. Our paper casts doubt on this misconception by examining the dynamics between social media customer complaints and brand service interventions. We find service interventions indeed cause more complaints, yet this increase is driven by service awareness rather than chronic complaining. Due to the publicity and connectivity of social media, customers learn about the new service channel by observing customer service delivery to others – a mechanism that is unique to social media customer service and does not …

Challenges When Identifying Migration From Geo-Located Twitter Data, Caitrin Armstrong, Ate Poorthuis, Matthew Zook, Derek Ruths, Thomas Soehl

Geography Faculty Publications

Given the challenges in collecting up-to-date, comparable data on migrant populations the potential of digital trace data to study migration and migrants has sparked considerable interest among researchers and policy makers. In this paper we assess the reliability of one such data source that is heavily used within the research community: geolocated tweets. We assess strategies used in previous work to identify migrants based on their geolocation histories. We apply these approaches to infer the travel history of a set of Twitter users who regularly posted geolocated tweets between July 2012 and June 2015. In a second step we hand-code …

Brexit: Psychometric Profiling The Political Salubrious Through Machine Learning: Predicting Personality Traits Of Boris Johnson Through Twitter Political Text, James Usher, Pierpaolo Dondio

Conference papers

Whilst the CIA have been using psychometric profiling for decades, Cambridge Analytica showed that people's psychological characteristics can be accurately predicted from their digital footprints, such as their Facebook or Twitter accounts. To exploit this form of psychological assessment from digital footprints, we propose machine learning methods for assessing political personality from Twitter. We have extracted the tweet content of Prime Minster Boris Johnson’s Twitter account and built three predictive personality models based on his Twitter political content. We use a Multi-Layer Perceptron Neural network, a Naive Bayes multinomial model and a Support Machine Vector model to predict the OCEAN …

@Houstonpolice: An Exploratory Case Of Twitter During Hurricane Harvey, Seungwon Yang, Brenton Stewart

Faculty Publications

Abstract

Purpose

The purpose of this paper is to examine the Houston Police Department (HPD)’s public engagement efforts using Twitter during Hurricane Harvey, which was a large-scale urban crisis event.

Design/methodology/approach

This study harvested a corpus of over 13,000 tweets using Twitter’s streaming API, across three phases of the Hurricane Harvey event: preparedness, response and recovery. Both text and social network analysis (SNA) techniques were employed including word clouds, n-gram analysis and eigenvector centrality to analyze data.

Findings

Findings indicate that departmental tweets coalesced around topics of protocol, reassurance and community resilience. Twitter accounts of governmental agencies, such as …

Analysis Of Flickr, Snapchat, And Twitter Use For The Modeling Of Visitor Activity In Florida State Parks, Hartwig H. Hochmair, Levente Juhasz

GIS Center

Spatio-temporal information attached to social media posts allows analysts to study human activity and travel behavior. This study analyzes contribution patterns to the Flickr, Snapchat, and Twitter platforms in over 100 state parks in Central and Northern Florida. The first part of the study correlates monthly visitor count data with the number of Flickr images, snaps, or tweets, contributed within the park areas. It provides insight into the suitability of these different social media platforms to be used as a proxy for the prediction of visitor numbers in state parks. The second part of the study analyzes the spatial distribution …

View, Like, Comment, Post: Analyzing User Engagement By Topic At 4 Levels Across 5 Social Media Platforms For 53 News Organizations, Kholoud K. Aldous, Jisun An, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

We evaluate the effects of the topics of social media posts on audiences across five social media platforms (i.e., Facebook, Instagram, Twitter, YouTube, and Reddit) at four levels of user engagement. We collected 3,163,373 social posts from 53 news organizations across five platforms during an 8month period. We analyzed the differences in news organization platform strategies by focusing on topic variations by organization and the corresponding effect on user engagement at four levels. Findings show that topic distribution varies by platform, although there are some topics that are popular across most platforms. User engagement levels vary both by topics and …

Twitter And Disasters: A Social Resilience Fingerprint, Benjamin A. Rachunok, Jackson B. Bennett, Roshanak Nateghi

Purdue University Libraries Open Access Publishing Fund

Understanding the resilience of a community facing a crisis event is critical to improving its adaptive capacity. Community resilience has been conceptualized as a function of the resilience of components of a community such as ecological, infrastructure, economic, and social systems, etc. In this paper, we introduce the concept of a “resilience fingerprint” and propose a multi-dimensional method for analyzing components of community resilience by leveraging existing definitions of community resilience with data from the social network Twitter. Twitter data from 14 events are analyzed and their resulting resilience fingerprints computed. We compare the fingerprints between events and show that …

The Global Disinformation Order: 2019 Global Inventory Of Organised Social Media Manipulation, Samantha Bradshaw, Philip N. Howard

Copyright, Fair Use, Scholarly Communication, etc.

Executive Summary

Over the past three years, we have monitored the global organization of social media manipulation by governments and political parties. Our 2019 report analyses the trends of computational propaganda and the evolving tools, capacities, strategies, and resources.

1. Evidence of organized social media manipulation campaigns which have taken place in 70 countries, up from 48 countries in 2018 and 28 countries in 2017. In each country, there is at least one political party or government agency using social media to shape public attitudes domestically.

2.Social media has become co-opted by many authoritarian regimes. In 26 countries, computational propaganda …

Web Archives At The Nexus Of Good Fakes And Flawed Originals, Michael L. Nelson

Computer Science Faculty Publications

[Summary] The authenticity, integrity, and provenance of resources we encounter on the web are increasingly in question. While many people are inured to the possibility of altered images, the easy accessibility of powerful software tools that synthesize audio and video will unleash a torrent of convincing “deepfakes” into our social discourse. Archives will no longer be monopolized by a countable number of institutions such as governments and publishers, but will become a competitive space filled with social engineers, propagandists, conspiracy theorists, and aspiring Hollywood directors. While the historical record has never been singular nor unmalleable, current technologies empower an unprecedented …

Recommending Who To Follow In The Software Engineering Twitter Space, Abhabhisheksh Sharma, Yuan Tian, Agus Sulistya, Dinusha Wijedasa, David Lo

Research Collection School Of Computing and Information Systems

With the advent of social media, developers are increasingly using it in their software development activities. Twitter is one of the popular social mediums used by developers. A recent study by Singer et al. found that software developers use Twitter to “keep up with the fast-paced development landscape.” Unfortunately, due to the general-purpose nature of Twitter, it’s challenging for developers to use Twitter for their development activities. Our survey with 36 developers who use Twitter in their development activities highlights that developers are interested in following specialized software gurus who share relevant technical tweets.To help developers perform this task, in …

Offline Versus Online: A Meaningful Categorization Of Ties For Retweets, Felicia Natali, Feida Zhu

Research Collection School Of Computing and Information Systems

With the recent proliferation of news being shared through online social networks, it is crucial to determine how news is spread and what drives people to share certain stories. In this paper, we focus on the social networking site Twitter and analyse user’s retweets. We study retweeting patterns between offline and online friends, particularly, how tweet novelty and tweet topic differ between tweets retweeted by offline friends and those retweeted by online friends.

Assessing Relevance Of Tweets For Risk Communication, Xiaohui Liu, Bandana Kar, Chaoyang Zhang, David M. Cochran

Faculty Publications

Although Twitter is used for emergency management activities, the relevance of tweets during a hazard event is still open to debate. In this study, six different computational (i.e. Natural Language Processing) and spatiotemporal analytical approaches were implemented to assess the relevance of risk information extracted from tweets obtained during the 2013 Colorado flood event. Primarily, tweets containing information about the flooding events and its impacts were analysed. Examination of the relationships between tweet volume and its content with precipitation amount, damage extent, and official reports revealed that relevant tweets provided information about the event and its impacts rather than any …

Temporal And Spatiotemporal Investigation Of Tourist Attraction Visit Sentiment On Twitter, Jose J. Padilla, Hamdi Kavak, Christopher J. Lynch, Ross J. Gore, Saikou Y. Diallo

VMASC Publications

In this paper, we propose a sentiment-based approach to investigate the temporal and spatiotemporal effects on tourists' emotions when visiting a city's tourist destinations. Our approach consists of four steps: data collection and preprocessing from social media; visitor origin identification; visit sentiment identification; and temporal and spatiotemporal analysis. The temporal and spatiotemporal dimensions include day of the year, season of the year, day of the week, location sentiment progression, enjoyment measure, and multi-location sentiment progression. We apply this approach to the city of Chicago using over eight million tweets. Results show that seasonal weather, as well as special days and …

Inferring Social Media Users’ Demographics From Profile Pictures: A Face++ Analysis On Twitter Users, Soon-Gyo Jung, Jisun An, Haewoon Kwak, Joni Salminen, Bernard J. Jansen

Research Collection School Of Computing and Information Systems

In this research, we evaluate the applicability of using facial recognition of social media account profile pictures to infer the demographic attributes of gender, race, and age of the account owners leveraging a commercial and well-known image service, specifically Face++. Our goal is to determine the feasibility of this approach for actual system implementation. Using a dataset of approximately 10,000 Twitter profile pictures, we use Face++ to classify this set of images for gender, race, and age. We determine that about 30% of these profile pictures contain identifiable images of people using the current state-of-the-art automated means. We then employ …

Demographics Of News Sharing In The U.S. Twittersphere, Julio C.S. Reis, Haewoon Kwak, Jisun An, Johnnatan Messias, Benevenuto Fabrıcio.

Research Collection School Of Computing and Information Systems

The widespread adoption and dissemination of online news through social media systems have been revolutionizing many segments of our society and ultimately our daily lives. In these systems, users can play a central role as they share content to their friends. Despite that, little is known about news spreaders in social media. In this paper, we provide the first of its kind in-depth characterization of news spreaders in social media. In particular, we investigate their demographics, what kind of content they share, and the audience they reach. Among our main findings, we show that males and white users tend to …

Marketing The Mountain State: A Large N Study Of User Engagement On Twitter, Kirk Richardson

Capstone Projects – Politics and Government

Much of the evolving research on the use of social media in destination marketing emphasizes how information diffusion influences the reputational image of place. The present study uses Twitter data to focus on the relative differences in user engagement across discrete account types. Specifically, this is done to examine how the official destination marketing organization of Montana—the Montana Office of Tourism (MTOT)—performs relative to other account types. Several regression analyses conducted on Twitter data associated with an ongoing MTOT place branding campaign reveal that tweets sent from ‘official’ accounts are more likely to be retweeted, and are estimated to receive …

The Retransmission Of Rumor And Rumor Correction Messages On Twitter, Alton Y. K. Chua, Cheng-Ying Tee, Augustine Pang, Ee-Peng Lim

Research Collection Lee Kong Chian School Of Business

This article seeks to examine the relationships among source credibility, message plausibility, message type (rumor or rumor correction) and retransmission of tweets in a rumoring situation. From a total of 5,885 tweets related to the rumored death of the founding father of Singapore Lee Kuan Yew, 357 original tweets without an “RT” prefix were selected and analyzed using negative binomial regression analysis. The results show that source credibility and message plausibility are correlated with retransmission. Also, rumor correction tweets are retweeted more than rumor tweets. Moreover, message type moderates the relationship between source credibility and retransmission as well as that …

Infodemiology For Syndromic Surveillance Of Dengue And Typhoid Fever In The Philippines, Ma. Regina Justina E. Estuar, Kennedy E. Espina

Department of Information Systems & Computer Science Faculty Publications

Finding determinants of disease outbreaks before its occurrence is necessary in reducing its impact in populations. The supposed advantage of obtaining information brought by automated systems fall short because of the inability to access real-time data as well as interoperate fragmented systems, leading to longer transfer and processing of data. As such, this study presents the use of realtime latent data from social media, particularly from Twitter, to complement existing disease surveillance efforts. By being able to classify infodemiological (health-related) tweets, this study is able to produce a range of possible disease incidences of Dengue and Typhoid Fever within the …

Efficient Online Summarization Of Large-Scale Dynamic Networks, Qiang Qu, Siyuan Liu, Feida Zhu, Christian S. Jensen

Research Collection School Of Computing and Information Systems

Information diffusion in social networks is often characterized by huge participating communities and viral cascades of high dynamicity. To observe, summarize, and understand the evolution of dynamic diffusion processes in an informative and insightful way is a challenge of high practical value. However, few existing studies aim to summarize networks for interesting dynamic patterns. Dynamic networks raise new challenges not found in static settings, including time sensitivity, online interestingness evaluation, and summary traceability, which render existing techniques inadequate. We propose dynamic network summarization to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or …

‘Tweetboard’ – A Case Study Of Developing A Micro-Blogging Platform For Higher Education, Shao Cheh Joyce Hsu, Gan, Benjamin, Jin Lee, Shu Hui Sheryl Lim, Xie Yan Jeremy Lim, Thomas Menkhoff, Si Xian Sherman Tan, Charles Jason Woodard, Qiu Cheng Yap

Research Collection School Of Computing and Information Systems

This paper reports experiences made at an Asian university in developing a social media platform based on Twitter in the context of a final year capstone project where information systems management students get an opportunity to solve ‘a real-world problem for a real client’. In this case study, the challenge was provided by a faculty member’s request for an interactive social media application which engages less outspoken students in class via a social medium they are familiar with: Twitter. We reconstruct the project’s evolution; describe the main features of the application called ‘TweetBoard’ and share lessons learned in developing a …

Detecting Community Pacemakers Of Burst Topic In Twitter, Guozhong Dong, Wu Yang, Feida Zhu, Wei Wang

Research Collection School Of Computing and Information Systems

Twitter has become one of largest social networks for users to broad-cast burst topics. Influential users usually have a large number of followers and play an important role in the diffusion of burst topic. There have been many studies on how to detect influential users. However, traditional influential users detection approaches have largely ignored influential users in user community. In this paper, we investigate the problem of detecting community pacemakers. Community pacemakers are defined as the influential users that promote early diffusion in the user community of burst topic. To solve this problem, we present DCPBT, a framework that can …

Extending The Network: The Influence Of Offline Friendship On Twitter Network, Young Soo Kim, Kyungsub Stephen Choi, Felicia Natali

Research Collection School Of Computing and Information Systems

Twitter effectively provides a communication platform that allows users to strengthen or augment relationships with their close ones. It is a common scene to see groups of people in continuing group communication from offline to online using tools such as Twitter. Furthermore, it is also possible to meet new friends via online encounter. Under these circumstances, there would be friends who are both offline and online, or only in online. Many of earlier Twitter network studies focused on the network effects’ direction going from online to offline network. This paper explores the opposite direction, going from offline to online network. …

Can Instagram Posts Help Characterize Urban Micro-Events?, Kasthuri Jayarajah, Archan Misra

Research Collection School Of Computing and Information Systems

Social media content, from platforms such as Twitter and Foursquare, has enabled an exciting new field of social sensing, where participatory content generated by users has been used to identify unexpected emerging or trending events. In contrast to such text-based channels, we focus on image-sharing social applications (specifically Instagram), and investigate how such urban social sensing can leverage upon the additional multi-modal, multimedia content. Given the significantly higher fraction of geotagged content on Instagram, we aim to use such channels to go beyond identification of long-lived events (e.g., a marathon) to achieve finer-grained characterization of multiple micro-events (e.g., a person …

Collective Rumor Correction On The Death Hoax Of A Political Figure In Social Media, Alton Y. K. Chua, Sin-Mei Cheah, Dion Hoe-Lian Goh, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Conversations on social media networks that discuss a crisis incident as it unfolds have become a norm in recent years. Left to its own devices, such conversations could quickly degenerate into rumor mills. Little research has thus far examined the correction of rumors on social media. Using the third person effect as a theoretical underpinning, we developed a model of collective rumor correction on social media based on an incident surrounding the death hoax of a political figure. Tweets from Twitter were collected and analyzed for the period when a spike of circulating rumors speculating the demise of Singapore's first …

#Greysanatomy Vs. #Yankees: Demographics And Hashtag Use On Twitter, Jisun An, Ingmar Weber

Research Collection School Of Computing and Information Systems

Demographics, in particular, gender, age, and race, are a key predictor of human behavior. Despite the significant effect that demographics plays, most scientific studies using online social media do not consider this factor, mainly due to the lack of such information. In this work, we use state-of-the-art face analysis software to infer gender, age, and race from profile images of 350K Twitter users from New York. For the period from November 1, 2014 to October 31, 2015, we study which hashtags are used by different demographic groups. Though we find considerable overlap for the most popular hashtags, there are also …